Eating‐disorder symptoms and syndromes in a sample of urban‐dwelling Canadian women: Contributions toward a population health perspective
Bibliographic record
Abstract
OBJECTIVE: We estimated the prevalence of eating disorders and maladaptive eating behaviors in a population-based sample and examined the association of maladaptive eating with self-rated physical and mental health. METHOD: A sample of 1,501 women (mean age = 31.2 years, SD = 6.2) were recruited using random-digit dialing to participate in a 20-min telephone interview about eating behaviors. RESULTS: Weighted frequency analysis showed the prevalence of frequent binge-eating to be 4.1%, that of regular purging to be 1.1%, and that of frequent compensation to be 8.7%. Although we found none of the women to meet full criteria for anorexia nervosa, 0.6% met criteria for bulimia nervosa, 3.8% provisional criteria for binge eating disorder, and 0.6% criteria for a newly proposed entity, purging disorder. As many as 14.9% fell into a residual category representing subthreshold, but potentially problematic variants of eating disturbances. Logistic regression analyses showed that clinical-level maladaptive eating attitudes and behaviors predicted self-rated physical- and mental-health problems after sociodemographic factors were controlled. DISCUSSION: This population-based survey provides prevalence estimates of BN, BED, and purging disorder that are compatible with those of recent epidemiological studies and shows that maladaptive eating attitudes and behaviors represent a substantial population burden.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".